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The Omniscribe Codify API provides AI-powered ICD-10 medical coding from clinical notes, with 77% greater accuracy than general-purpose LLMs. In simple terms: you send a clinical note (text or PDF), and the API returns structured ICD-10 code assessments with confidence scores, justifications, and detailed analysis of the AI’s decision-making process.

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Why We Are Different

Unlike general-purpose LLMs (such as ChatGPT, Claude, etc.), we use specialized models trained specifically for clinical coding, achieving:
  • 77% higher accuracy than general LLMs in ICD-10 coding.
  • A 92% reduction in medical hallucinations.
  • Customization for your center: Personalized models trained on your nomenclatures and workflows.
  • Truly multilingual: Trained on clinical Spanish, Catalan, Basque, Galician, and English.

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What Is It For?

This API solves critical clinical documentation challenges:

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ICD-10 Medical Coding

  • Automatic ICD-10 code extraction from clinical notes with AI-powered analysis.
  • Confidence scores for each code (0-100%) to support coding decisions.
  • Detailed justifications explaining why each code was selected.
  • Discarded codes analysis showing rejected codes and reasoning.
  • Measurable ROI: A 70% reduction in coding time.

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Billing and Compliance

  • Accurate code assignments for reimbursement.
  • Audit trail with run_id tracking for each coding session.
  • Doctor and patient tracking for regulatory compliance.
  • Quality assurance through transparent AI decision-making.

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Integration Ready

  • PDF support for processing scanned documents (up to 5MB).
  • Text input for direct EHR integration (up to 50KB).
  • Custom AI models selection for specialized needs.
  • RESTful API with consistent error handling.

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How Does the Process Work?

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Step 1: Prepare Your Clinical Note

Prepare your clinical note as either:
  • Plain text (up to 50KB) - from EHR, dictation, or manual entry
  • PDF file (up to 5MB decoded) - scanned documents or reports
Optionally, specify a custom AI model for specialized processing needs.

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Step 2: Send to the Codify API

Send your clinical note to /v1/codify with optional tracking headers for audit purposes. Our specialized clinical AI engine:
  1. Analyzes the medical context using models trained on millions of real clinical notes.
  2. Identifies diagnoses and medical conditions with high accuracy.
  3. Assigns appropriate ICD-10 codes with confidence scores.
  4. Provides detailed justifications for each code selection.
  5. Shows discarded codes and why they were rejected.

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Step 3: Receive ICD-10 Code Assessments

The API returns:
  • Final code assessments: Selected ICD-10 codes with descriptions, justifications, and confidence scores
  • Discarded assessments: Rejected codes showing the AI’s decision-making process
  • Run ID: Unique identifier for tracking and debugging
Key advantage: Complete transparency with confidence scores and justifications helps coders make informed decisions and maintain quality standards.

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Available Endpoints

POST /v1/codify

Codes clinical text into a JSON structure that you define.

GET /v1/health

Verifies that the service is operational.

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API Versioning

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Versioning Scheme

  • Path versioning: /v1/, /v2/, etc.
  • Backward-compatible changes: Are added to the current version without breaking the API.
  • Breaking changes: Increment the major version (e.g., v1 → v2).
Current version: v1.0.0 — Initial release of the public endpoint.

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Next Steps

1. Quickstart

Your first API call

2. Authentication

Configuring tokens and headers

3. Data Structure

Requests and responses

4. View Examples

Practical coding examples

5. Operations and Errors

Error handling and security

6. Complete Reference

OpenAPI specification